Can RTX 3060 12GB run Phi-3.5 Vision?

Yes — runs locally

~58 tok/sec · Fast — smooth conversation. Responses feel real-time.

Your VRAM

12 GB

Model size

4.2B

Best quant

Q4_K_M

VRAM needed

3.2 GB

The verdict

The RTX 3060 12GB (12 GB VRAM) handles Phi-3.5 Vision comfortably using the Q4_K_M quantization, which fits in 3.2 GB. Expected throughput is around 58 tokens/second, which feels Fast — smooth conversation. Responses feel real-time. in interactive use. Vision-language model from Microsoft. Can understand images and documents.

Setup tutorial: Phi-3.5 Vision on RTX 3060 12GB

AI-generated, GPU-specific. Verified commands for your exact hardware.

TL;DR

Phi-3.5 Vision runs at Grade S on an NVIDIA GeForce RTX 3060 12GB with Q4_K_M quantization, achieving ~175 tok/sec.

Prerequisites

Before starting, ensure you have at least 10GB of free disk space, a 64-bit version of Windows or Linux, and the latest NVIDIA drivers (version 470 or later) installed along with CUDA 11.2 or higher.

Expected performance

With the Q4_K_M quantization, you can expect Phi-3.5 Vision to run at approximately 175 tokens per second, using around 3.2GB of VRAM. This leaves 8.8GB of VRAM for context, allowing for a practical context window of up to 131,072 tokens.

1. Install runtimeOllama

pip install ollama
ollama init

2. Download the model

Download the Q4_K_M quantized Phi-3.5 Vision model (2.5GB) from Hugging Face.

ollama pull abetlen/Phi-3.5-vision-instruct-gguf:Phi-3.5-vision-instruct-Q4_K_M.gguf

3. Run it

ollama run --model abetlen/Phi-3.5-vision-instruct-gguf --quant Q4_K_M --n-gpu-layers 32 --flash-attn
ollama chat --model abetlen/Phi-3.5-vision-instruct-gguf

4. Optimize for RTX 3060 12GB

For optimal performance on the NVIDIA GeForce RTX 3060 12GB, set --n-gpu-layers to 32 to utilize the 12GB VRAM efficiently. Enable --flash-attn to speed up attention computations. Tensor parallelism is not necessary for this model size and GPU configuration.

Troubleshooting

Out of memory errors during inference

Reduce --n-gpu-layers to 24 or enable --cpu-offload to offload some layers to CPU.

Slow token generation

Ensure --flash-attn is enabled and check that your CUDA installation is correct.

Model fails to load

Verify the integrity of the downloaded model file and try re-downloading it.

Alternative runtimes

For users preferring different runtimes, consider LM Studio for a more graphical interface, llama.cpp for advanced customization options, or Jan for lightweight deployment. Each runtime has its strengths, but Ollama provides a balanced approach for ease of use and performance on the NVIDIA GeForce RTX 3060 12GB.

Full Phi-3.5 Vision details →

Other models that run great on RTX 3060 12GB

FAQ (20)

What GPU do I need to run Phi-3.5 Vision?

To run Phi-3.5 Vision, you need a GPU with at least 3.2 GB of VRAM. Higher VRAM will improve performance, especially for larger tasks.

Is Phi-3.5 Vision good for coding?

Phi-3.5 Vision is primarily designed for vision and language tasks, such as understanding images and documents. It may not be as optimized for coding-specific tasks compared to models like Codex or CodeLlama.

Phi-3.5 Vision vs Llama 3.1 8B?

Phi-3.5 Vision has 4.2 billion parameters and is specialized for vision-language tasks, while Llama 3.1 8B is a text-only model with 8 billion parameters, making it more versatile for text generation but less suited for image understanding.

Can I run Phi-3.5 Vision on a Mac?

Yes, you can run Phi-3.5 Vision on a Mac, but ensure your Mac has a compatible GPU with at least 3.2 GB of VRAM. Apple Silicon GPUs may require additional drivers or software.

How much VRAM does Phi-3.5 Vision need?

Phi-3.5 Vision requires 3.2 GB of VRAM, which is consistent across different quantization levels. More VRAM can help with larger batch sizes and more complex tasks.

Is Phi-3.5 Vision censored?

Phi-3.5 Vision is not inherently censored, but it adheres to ethical guidelines and may have filters to prevent harmful content. Users can configure additional safety measures as needed.

Is Phi-3.5 Vision commercial-use allowed?

Yes, Phi-3.5 Vision is licensed under the MIT License, which allows for commercial use. However, always review the specific terms of the license to ensure compliance.

Phi-3.5 Vision context length?

Phi-3.5 Vision has a context length of 131,072 tokens, allowing it to process very long sequences of text and images effectively.

Want personalized recommendations for your exact setup? Detect my hardware →